Excess water availability in northern mid-high latitudes contiguously migrated from ocean under climate change

Yansong Guan^{1

2}, Xihui Gu^{1

2}, Lunche Wang^{1

2}, Tianjun Zhou^{3

4}, Jun Xia⁵, Dabang Jiang³, Louise J Slater⁶, Luis Gimeno^{7

8}, Yadu Pokhrel⁹, Gabriele Villarini^{10

11}, Jong-Seong Kug¹², Seok-Woo Son¹², Richard P Allan¹³, Jianfeng Li¹⁴, Thian Yew Gan¹⁵, Yinxue Liu^{6

16}, Dongdong Kong¹⁷, Xiang Zhang¹⁸, Xiangsen Cui¹

Affiliations

¹ State Key Laboratory of Geomicrobiology and Environmental Changes, China University of Geosciences, Wuhan, China.
² Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China.
³ Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
⁴ University of the Chinese Academy of Sciences, Beijing, China.
⁵ State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China.
⁶ School of Geography and the Environment, University of Oxford, Oxford, UK.
⁷ Centro de Investigaciόn Mariña, Environmental Physics Laboratory, Universidade de Vigo, Ourense, Spain.
⁸ Galician Supercomputing Center (CESGA), Santiago de Compostela, Spain.
⁹ Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, USA.
¹⁰ Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA.
¹¹ High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA.
¹² School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea.
¹³ Department of Meteorology and National Centre for Earth Observation, University of Reading, Reading, UK.
¹⁴ Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
¹⁵ Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB, Canada.
¹⁶ Geography and Environment, Loughborough University, Loughborough, UK.
¹⁷ Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China.
¹⁸ National Engineering Research Center of Geographic Information System, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China.

PMID: 40802764
PMCID: PMC12346308
DOI: 10.1126/sciadv.adv0282

Excess water availability in northern mid-high latitudes contiguously migrated from ocean under climate change

Yansong Guan et al. Sci Adv. 2025.

. 2025 Aug 15;11(33):eadv0282.

doi: 10.1126/sciadv.adv0282. Epub 2025 Aug 13.

Authors

Affiliations

¹ State Key Laboratory of Geomicrobiology and Environmental Changes, China University of Geosciences, Wuhan, China.
² Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China.
³ Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
⁴ University of the Chinese Academy of Sciences, Beijing, China.
⁵ State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China.
⁶ School of Geography and the Environment, University of Oxford, Oxford, UK.
⁷ Centro de Investigaciόn Mariña, Environmental Physics Laboratory, Universidade de Vigo, Ourense, Spain.
⁸ Galician Supercomputing Center (CESGA), Santiago de Compostela, Spain.
⁹ Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, USA.
¹⁰ Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA.
¹¹ High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA.
¹² School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea.
¹³ Department of Meteorology and National Centre for Earth Observation, University of Reading, Reading, UK.
¹⁴ Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
¹⁵ Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB, Canada.
¹⁶ Geography and Environment, Loughborough University, Loughborough, UK.
¹⁷ Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China.
¹⁸ National Engineering Research Center of Geographic Information System, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China.

PMID: 40802764
PMCID: PMC12346308
DOI: 10.1126/sciadv.adv0282

Abstract

Terrestrial water availability sustains livelihoods, socioeconomic development, and ecosystems. Despite an understanding of contributions of oceanic moisture to terrestrial hydroclimatic extremes, whether surpluses of terrestrial water availability migrate directly and contiguously from the ocean and the influence of climate change on this process remain unclear. Here, we use a coherent feature-tracking method to identify ocean-to-land water availability surpluses (OWASs), characterized by spatiotemporally contiguous migration of excess atmospheric freshwater (precipitation-minus-evapotranspiration) from ocean to land. Over the past several decades, especially in northern mid-high latitudes (NMHL; above 48°N), OWASs have exhibited longer persistence, wider areal extent, and greater intensity than those developed solely over land. These landward migrations are associated with seasonal Atlantic teleconnection and Pacific circulation shift. Under the business-as-usual scenario, these two processes are projected to be enhanced, markedly increasing OWAS characteristics in NMHL driven by thermodynamic atmospheric responses to future warming. Intensified OWASs may not only help alleviate long-term droughts but also have the potential to accentuate pluvial risks.

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Figures

**Fig. 1.. Climatological characteristics of OWAS during 1961–2020.**
(A) Three-dimensional evolution of OWAS and OWAS-propagated spatiotemporally contiguous TWS pluvial during August 2006–September 2007. (B) Maps show the frequency of OWASs (top) from ERA5 and OWAS-propagated TWS pluvial events (bottom) from GTWS-MLrec globally during 1961–2020. (C to K) Same as (B), but for duration [(C) to (E)], intensity [(F) to (H)], and areal extent [(I) to (K)] of OWASs from ERA5 and the CMIP6 multimodel mean, as well as those of OWAS-propagated TWS pluvial events from GTWS-MLrec. The bottom-left inset boxplots in [(C), (F), and (I)] represent the characteristics of OWASs and land-originating water availability surpluses from ERA5, 32 CMIP6 models, and 50 CanESM5 ensemble members. The inset scatterplots in [(D), (G), and (J)] represent the OWAS characteristics in each grid cell from CMIP6 multimodel mean and ERA5. The symbol “RE” indicates the relative error. The lines accompanying the maps in [(D), (G), and (J)] show the zonal means of the climatological OWAS characteristics from ERA5, CMIP6, and CanESM5. The blue (purple) shading shows the spread of zonal mean values for 90% of the CMIP6 models (CanESM5 ensemble members). The inset boxplots in [(E), (H), and (K)] represent the characteristics of OWAS-propagated TWS pluvial events and other TWS pluvial events. Symbol “*” indicates a significant difference between distributions (Kolmogorov-Smirnov test, P < 0.05) or a significant correlation (Pearson’s correlation, P < 0.001). The top to bottom boxplot bounds represent the value of Q3 + 1.5 × IQR, third quartile (Q3), median (horizontal line), first quartile (Q1), and Q1 − 1.5 × IQR, respectively, where IQR denotes the interquartile range (Q3 − Q1).

**Fig. 2.. Human-induced relative changes in OWAS characteristics during 1921–2020.**
(A to D) Maps show the relative changes in frequency (A), duration (B), intensity (C), and areal extent (D) of OWASs based on CMIP6 under GHG effects over the globe during 1981–2010. Stippling indicates that more than 60% of the models agree on the changes in OWAS characteristics across CMIP6 models. Black boxes in maps include 21 different Giorgi climate regions. Heatmaps show regional relative changes in OWAS characteristics across 30-year moving windows from 1921 to 2020 under AER compared to under ALL in different climate regions. The label “2020” corresponds to the 1991–2020 window. GRL, Greenland and Northern Territories; ALA, Alaska; NEU, Northern Europe; NAS, North Asia; WNA, Western North America; TIB, Tibet; CAS, Central Asia; CNA, Central North America; MED, Mediterranean Basin; ENA, Eastern North America; EAS, East Asia; SAH, Sahara; CAM, Central America; SAS, South Asia; SEA, Southeast Asia; EAF, Eastern Africa; WAF, Western Africa; AMZ, Amazon Basin; SAF, Southern Africa; AUS, Australia; SSA, Southern South America.

**Fig. 3.. Landward migration routes and mechanisms of OWASs in NMHL from the northern Atlantic and northeastern Pacific.**
(A) Maps show water availability (PME) anomalies where the SWAI > 0.8 from December to August under CMIP6 ALL during 1961–2020. Heatmap shows longitudinal accumulation of monthly WAAs in the northern Atlantic and northern Eurasia. (B) Maps show composite anomalies of integrated moisture flux and cumulative WAAs over the northeastern Pacific and western North America between ALL during OWAS pre–land (top) or post–land (bottom) arrival period (1961–2020) and the climatological mean (1981–2010). The OWAS pre–land arrival period is the period from genesis to arrive at land. The OWAS post–land arrival period is the period from arriving land to extinction. (C) Map shows the cumulative WAAs from the northern Atlantic to northern Eurasia and from the northeastern Pacific to western North America during 1961–2020. Red and blue contours indicate areas where the cumulative WAAs over the northeastern Pacific exceed 500 mm month⁻¹ during the pre–land arrival and post–land arrival period. (D and E) Maps show winter SST trends in the northern Atlantic during 1961–2020 (D), as well as composite sea level pressure anomalies in the northeastern Pacific during the pre–land arrival (E) and post–land arrival (D) period compared to the climatological mean, respectively.

**Fig. 4.. Projected relative changes in OWAS characteristics under SSP585.**
(A to D) Maps show projected relative changes in OWAS frequency (A), duration (B), intensity (C), and areal extent (D) between CMIP6 SSP585 during 2071–2100 and ALL during 1981–2010, respectively. Stippling indicates that more than 60% of the models agree on the changes in OWAS characteristics across CMIP6 models. Bar charts in maps [(A) to (D)] present OWAS characteristics for each risk level. Heatmaps accompanying the maps [(A) to (D)] show regional relative changes in 30-year moving windows under ALL + SSP585 during 1921–2100 compared to ALL during 1981–2010 in different climate regions, with “2100” representing the window of 2071–2100. Symbol “▼” indicates climate regions where the |SNR| > 1. (E) Map shows OWAS risk levels globally from CMIP6 SSP585 during 2071–2100. Bar chart represents the proportion of each climate region in different OWAS risk levels. (F) Thermodynamic, dynamic, and nonlinear components of normalized differences in moisture flux convergence (MFC) during OWASs between CMIP6 SSP585 during 2071–2100 and ALL during 1981–2010. Map shows the dominant MFC component in each grid cell. Hatchings on the maps show regions where the thermodynamic component dominates. Bar chart shows the contribution of each component in a climate region.

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Excess water availability in northern mid-high latitudes contiguously migrated from ocean under climate change

Affiliations

Excess water availability in northern mid-high latitudes contiguously migrated from ocean under climate change

Authors

Affiliations

Abstract

Figures

References

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